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Shows enhanced V2X communication security in vehicle networks, suggesting better protection against modeling attacks.
The rapid growth of Intelligent Transportation Systems (ITSs) necessitates secure and efficient Vehicle-to-Everything (V2X) communication. However, existing Physical Unclonable Function (PUF)-based schemes often suffer from modeling vulnerabilities and high overheads. This paper proposes a decentralized, dynamic, anonymous authentication protocol tailored for Vehicular Ad Hoc Networks (VANETs). By integrating Elliptic Curve Cryptography (ECC) with highly reliable Self-Adaption Deviation Locking PUFs (SDL PUFs), we design a dynamic Challenge–Response Pair (CRP) obfuscation mechanism. This mechanism effectively mitigates modeling threats, reducing the prediction success rate of machine learning (ML) and deep learning (DL) attacks by approximately 35% compared to raw SDL PUFs. The protocol ensures identity untraceability and forward secrecy through anonymous identifiers and ephemeral session keys. Security is formally verified under the Real-or-Random (ROR) model and validated using the AVISPA tool. Simulations in SUMO and Omnetpp demonstrate that the protocol is highly efficient, achieving a low computational overhead of 6.77 ms per entity and a communication cost of 192 bytes. Compared to state-of-the-art approaches, our solution provides superior robustness against advanced modeling attacks and significantly reduces latency, making it suitable for resource-constrained V2X environments.
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Song et al. (2026) studied this question.
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